Simultaneous Retrieval of Land Surface Temperature and Soil Moisture Using Multichannel Passive Microwave Data

文献类型： 外文期刊

第一作者： Han, Xiao-Jing

作者： Han, Xiao-Jing;Chen, Xueyuan;Yao, Na;Wu, Zihao;Leng, Pei;Han, Wenjing;Wu, Zihao;Leng, Pei;Han, Wenjing

作者机构：

关键词： Land surface temperature; Atmospheric modeling; Land surface; Vegetation mapping; Soil moisture; Microwave theory and techniques; Mathematical models; Land surface temperature (LST); radiative transfer model; soil moisture (SM)

期刊名称：IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING （ 影响因子：8.2； 五年影响因子：8.8 ）

ISSN： 0196-2892

年卷期： 2024 年 62 卷

页码：

收录情况： SCI

摘要： Land surface temperature (LST) and soil moisture (SM) are two important parameters in land surface ecosystem at the regional and global scale. The accurate acquisition of LST and SM can benefit various fields, including agriculture and climate which are closely related to human life. The independent retrievals of LST and SM from passive microwave observations are mutually restricted and highly dependent on auxiliary data. To solve this problem, a simulation retrieval method of LST and SM was proposed based on the characteristics of multifrequency and dual-polarization. The simultaneous solution of LST and SM was realized by approximating and correcting the radiative transfer equation (RTE). The performance of the proposed method was evaluated using simulated data, resulting in a root mean square error (RMSE) of approximately 1.63 K and 0.063 m(3)/m(3) . This method was further used to retrieve LST and SM from advanced microwave scanning radiometer for EOS (AMSR-E) observations. The retrieved LST was compared to the MODIS LST product under clear sky, with an RMSE of 5.68 K. The retrieved LST was validated using the Integrated Surface Database (ISD) air temperature under cloudy sky, with an RMSE of 4.29 K. The accuracy of retrieved LST changes with the variation of vegetation. The retrieved SM was evaluated using the Climate Change Initiative (CCI) SM product and in situ observations. The result shows that the accuracy ranges from 0.0157 to 0.1115 m(3)/m(3 )with the change of vegetation. This study gives a feasible method to retrieve LST and SM simultaneously with reasonable accuracy.

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